code: def test_simple_multi_output_ablation(self) -> None:
      net = BasicModel_MultiLayer(multi_input_module=True)
      inp = torch.tensor([[0.0, 6.0, 0.0]])
      self._ablation_test_assert(
          net,
          net.multi_relu,
          inp,
          ([[0.0, 7.0, 7.0, 7.0]], [[0.0, 7.0, 7.0, 7.0]]),
      )
  
file_path: captum/tests/attr/layer/test_layer_ablation.py
imports: import unittest
  from typing import Any, List, Tuple, Union
  import torch
  from captum._utils.typing import BaselineType
  from captum.attr._core.layer.layer_feature_ablation import LayerFeatureAblation
  from tests.helpers.basic import assertTensorTuplesAlmostEqual, BaseTest
  from tests.helpers.basic_models import BasicModel_ConvNet_One_Conv, BasicModel_MultiLayer, BasicModel_MultiLayer_MultiInput
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 5 for calling the Test obj's underlying member method code with example usage: obj.test_simple_multi_output_ablation() without return types